Python API¶
The java
module provides facilities to use Java classes and objects from Python code.
Data types¶
Overview¶
Data types are converted between Python and Java as follows:
Java
null
corresponds to PythonNone
.The Java boolean, integer and floating point types correspond to Python
bool
,int
andfloat
respectively. When Java code uses a “boxed” type, auto-boxing is done when converting from Python to Java, and auto-unboxing when converting from Java to Python.Java
String
andchar
both correspond to Pythonstr
.A Java array is represented by a
jarray
object. Java array parameters and fields can also be implicitly converted from any sequence, except a string.All other Java objects are represented by a
jclass
object.
A jclass
or jarray
object received from Java will be represented in Python as its
actual run-time type, which is not necessarily the declared type of the method, field or
parameter the object was obtained from. It can be viewed as another compatible type using the
cast
function.
Primitives¶
A Python bool
, int
, float
or str
object can be passed directly to any compatible Java
method parameter or field.
However, Java has more primitive types than Python, so when more than one compatible integer or
floating-point overload is applicable for a method call, the longest one will be used.
Similarly, when a 1-character string is passed to a method which has overloads for both
String
and char
, the String
overload will be used.
If these rules do not give the desired result, the following wrapper classes can be used to select which Java primitive type you want to use:
-
class
java.
jboolean
(value)¶
-
class
java.
jbyte
(value, truncate=False)¶
-
class
java.
jshort
(value, truncate=False)¶
-
class
java.
jint
(value, truncate=False)¶
-
class
java.
jlong
(value, truncate=False)¶
-
class
java.
jfloat
(value, truncate=False)¶
-
class
java.
jdouble
(value, truncate=False)¶
-
class
java.
jchar
(value)¶
-
class
java.
jvoid
¶ jvoid
cannot be instantiated, but may be used as a return type when defining a static proxy.
For example, if p
is a PrintStream:
p.print(42) # will call print(long)
p.print(jint(42)) # will call print(int)
p.print(42.0) # will call print(double)
p.print(jfloat(42.0)) # will call print(float)
p.print("x") # will call print(String)
p.print(jchar("x")) # will call print(char)
The numeric type wrappers take an optional truncate
parameter. If this is set, any excess
high-order bits of the given value will be discarded, as with a cast in Java. Otherwise,
passing an out-of-range value to a wrapper class will result in an OverflowError
.
When these wrappers are used, Java overload resolution rules will be in effect for the wrapped
parameter. For example, a jint
will only be applicable to a Java int
or larger, and the
shortest applicable overload will be used.
Classes¶
Note
Rather than calling jclass
directly, it’s usually more convenient to use the
import hook.
-
java.
jclass
(cls_name)¶ Returns a Python class for a Java class or interface type. The name must be fully-qualified, using either Java notation (e.g.
java.lang.Object
) or JNI notation (e.g.Ljava/lang/Object;
). To refer to a nested or inner class, separate it from the containing class with$
, e.g.java.lang.Map$Entry
.If the class cannot be found, a
NoClassDefFoundError
is raised.
Java classes and objects can be used with normal Python syntax:
>>> Calendar = jclass("java.util.Calendar")
>>> c = Calendar.getInstance()
>>> c.getTimeInMillis()
1588934677166
>>> c.getTime()
<java.util.Date 'Fri May 08 11:44:37 GMT+01:00 2020'>
>>> c.get(Calendar.YEAR)
2020
>>> c.before(Calendar.getInstance())
True
Overloaded methods are resolved according to Java rules:
>>> from java.lang import String, StringBuffer
>>> sb = StringBuffer(1024)
>>> sb.append(True)
>>> sb.append(123)
>>> sb.append(cast(String, None))
>>> sb.append(3.142)
>>> sb.toString()
'true123null3.142'
If a method or field name clashes with a Python reserved word, it can be accessed by
appending an underscore, e.g. from
becomes from_
. The original name is still
accessible via getattr
.
Aside from attribute access, Java objects also support the following operations:
==
and!=
call equals.is
is equivalent to Java==
(i.e. it tests object identity).The equivalent of the Java syntax
ClassName.class
isClassName.getClass()
; i.e. thegetClass()
method can be called on a class as well as an instance.If a Java object implements a functional interface, then it can be called like a function using
()
syntax. This includes lambdas, method references, and any interface with a single abstract method, such asjava.lang.Runnable
. If an object implements more than one functional interface, you must usecast
to select the one you want, or simply call the method by name.
The Java class hierarchy is reflected in Python, e.g. if s
is a Java String
object, then
isinstance(s, Object)
and isinstance(s, CharSequence)
will both return True
. All array
and interface types are also considered subclasses of java.lang.Object
.
Arrays¶
-
java.
jarray
(element_type)¶ Returns a Python class for a Java array type. The element type may be specified as any of:
jarray
objects represent Java arrays. They support the standard Python sequence protocol,
including:
Getting and setting elements using
[]
syntax. Negative indices are supported.Getting and setting slices using
[:]
syntax. When getting a slice, a new array of the same type will be returned.Copying using the
copy
method. A new array of the same type will be returned.Getting length using
len
, and testing for emptiness usingbool
.Iteration using
for
, and searching usingin
.Since Java arrays are fixed-length, they do not support
append
,del
, or any other way of adding or removing elements.
All arrays are instances of java.lang.Object
, so they inherit the Object
implementations
of toString
, equals
and hashCode
. However, these default implementations are not very
useful, so the equivalent Python operations are defined as follows:
str
returns a representation of the array contents.==
and!=
can compare the contents of the array with any sequence.Like Python lists, Java array objects are not hashable in Python because they’re mutable.
Creating¶
There’s usually no need to create jarray
objects directly, because any sequence (except a
string) can be passed directly to a Java method or field which takes an array type.
However, where a method has multiple array-type overloads, you may need to disambiguate the
call. For example, if a class defines both f(long[] x)
and f(int[] x)
, then calling
f([1,2,3])
will fail with an ambiguous overload error. To call the int[]
overload, use
f(jarray(jint)([1,2,3]))
.
More examples:
# Python code // Java equivalent
jarray(jint)([1, 2, 3]) new int[] {1, 2, 3}
jarray(jarray(jint))([[1, 2], [3, 4]]) new int[][] {{1, 2}, {3, 4}}
jarray(String)(["Hello", "world"]) new String[] {"Hello", "world"}
jarray(jchar)("hello") new char[] {'h', 'e', 'l', 'l', 'o'}
You can also pass an integer to create an array filled with zero, false
or null
:
# Python code // Java equivalent
jarray(jint)(5) new int[5]
Converting¶
Java arrays of boolean
, byte
, short
, int
, long
, float
and double
all implement
the Python buffer protocol. So if you convert
a Java array to a NumPy array, it will automatically use the correct data type:
>>> a = jarray(jshort)([0, 32767])
>>> numpy.array(a)
array([ 0, 32767], dtype=int16)
Calling bytes
on an array will return its in-memory representation:
>>> a = jarray(jshort)([0, 32767])
>>> bytes(a)
b'\x00\x00\xff\x7f'
When converting a Python bytes
or bytearray
object to a Java byte[]
array,
there is an unsigned-to-signed conversion: Python values 128 to 255 will be mapped to Java
values -128 to -1:
>>> b = bytes([0, 127, 128, 255])
>>> jarray(jbyte)(b)
jarray('B')([0, 127, -128, -1])
Similarly, when converting a byte[]
array to a bytes
or bytearray
object, there
is a signed-to-unsigned conversion:
>>> a = jarray(jbyte)([0, 127, -128, -1])
>>> [int(x) for x in bytes(a)]
[0, 127, 128, 255]
Casting¶
-
java.
cast
(cls, obj)¶ Returns a view of the given object as the given class. The class must be one created by
jclass
orjarray
, or a JNI type signature for a class or array. The object must either be assignable to the given class, orNone
(representing Javanull
), otherwiseTypeError
will be raised.Situations where this could be useful are the same as those where you might use the Java cast syntax
(ClassName)obj
. By changing the apparent type of an object:Different members may be visible on the object.
A different overload may be chosen when passing the object to a method.
Import hook¶
The import hook allows you to write code like from java.lang import String
, which is
equivalent to String = jclass("java.lang.String")
.
Only the
from ... import
form is supported, e.g.import java.lang.String
will not work.Wildcard import is not supported, e.g.
from java.lang import *
will not work.Only classes and interfaces can be imported from Java, not packages, e.g.
import java.lang
andfrom java import lang
will not work. Similarly, Java packages are never added tosys.modules
.Nested and inner classes cannot be imported directly. Instead, import the outer class, and access the nested class as an attribute, e.g.
Outer.Nested
.
To avoid confusion, it’s recommended to avoid having a Java package and a Python module with the same name. However, this is still possible, subject to the following points:
Names imported from the Java package will not automatically be added as attributes of the Python module.
Imports from both languages may be intermixed, even within a single
from ... import
statement. If you attempt to import a name which exists in both languages, the value from Python will be returned. This can be worked around by accessing the Java name viajclass
. For example, if both Java and Python have a class namedcom.example.Class
, then you can access them like this:from com.example import Class as PythonClass JavaClass = jclass("com.example.Class")
Relative package syntax is supported. For example, within a Python module called
com.example.module
:from . import Class # Same as "from com.example import Class" from ..other.package import Class # Same as "from com.other.package import Class"
-
java.
set_import_enabled
(enable)¶ Sets whether the import hook is enabled. The import hook is enabled automatically when the
java
module is first loaded, so you only need to call this function if you want to disable it.
Inheriting Java classes¶
To allow Python code to be called from Java without using the Chaquopy Java API, you can inherit from Java classes in Python. To make your inherited class visible to Java code, a corresponding Java proxy class must be generated, and there are two ways of doing this:
A dynamic proxy uses the java.lang.reflect.Proxy mechanism to generate a Java class at runtime.
A static proxy uses a build-time tool to generate Java source code.
Dynamic proxy¶
-
java.
dynamic_proxy
(*implements)¶ If you use the return value of this function as the first base of a class declaration, then the java.lang.reflect.Proxy mechanism will be used to generate a Java class for it at runtime. All arguments must be Java interface types.
Dynamic proxy classes are implemented just like regular Python classes, but any method names defined by the given interfaces will be visible to Java. If Java code calls an interface method which is not implemented by the Python class, a PyException will be thrown.
Simple example:
>>> from java.lang import Runnable, Thread
>>> class R(dynamic_proxy(Runnable)):
... def __init__(self, name):
super().__init__()
self.name = name
... def run(self):
... print("Running " + self.name)
...
>>> r = R("hello")
>>> t = Thread(r)
>>> t.getState()
<java.lang.Thread$State 'NEW'>
>>> t.start()
Running hello
>>> t.getState()
<java.lang.Thread$State 'TERMINATED'>
For more examples, see the unit tests.
Dynamic proxy classes have the following limitations:
They cannot extend Java classes, only implement Java interfaces.
They cannot be referenced by name in Java source code.
They cannot be instantiated in Java, only in Python.
If you need to do any of these things, you’ll need to use a static proxy instead.
Static proxy¶
-
java.
static_proxy
(extends=None, *implements, package=None, modifiers='public')¶ If you use the return value of this function as the first base of a class declaration, and pass the containing module to the static proxy generator tool, then it will create a Java source file allowing the class to be instantiated and accessed by Java code.
extends
must be a Java class type. PassNone
if you only want to implement interfaces.All other positional arguments must be Java interface types to implement.
package
is the name of the Java package in which the Java class will be generated, defaulting to the same as the Python module name.modifiers
is described below.
To generate Java methods for the class, use the following decorators:
-
java.
method
(return_type, arg_types, *, modifiers='public', throws=None)¶ Generates a Java method.
return_type
must be a single Java type, orjvoid
.arg_types
must be a (possibly empty) list or tuple of Java types.modifiers
is a string which is copied to the generated Java declaration. For example, to make a method synchronized, you can passmodifiers="public synchronized"
.throws
is a list or tuple ofjava.lang.Throwable
subclasses.
All Java types must be specified as one of the following:
A Java class imported using the import hook.
One of the primitive types.
A
jarray
type.
Multiple decorators may be used on the same method, in which case multiple Java signatures will be generated for it (see notes below on overloading).
-
java.
Override
(return_type, arg_types, *, modifiers='public', throws=None)¶
-
java.
constructor
(arg_types, *, modifiers='public', throws=None)¶ Same as
method
, except it generates a Java constructor. This decorator can only be used on the__init__
method. Note there is no return type.
Simple example:
# Python code // Java equivalent
from com.example import Base, Iface1, Iface1 import com.example.*;
from java.lang import String, Exception
class C(static_proxy(Base, Iface1, Iface2)): class C extends Base implements Iface1, Iface2 {
@constructor([jint, String]) public C(int i, String s) {
def __init__(self, i, s): ...
... }
@method(jvoid, [jint], throws=[Exception]) public void f(int i) throws Exception {
...
}
@Override(String, [jint, String], @Override
modifiers="protected") protected String f(int i, String s) {
def f(self, i, s=None): ...
... }
}
For more examples, see the demo app and unit tests.
Because the static proxy generator works by static analysis of the Python source code, there are some restrictions on the code’s structure:
Only classses which appear unconditionally at the module top-level will be processed.
Java classes passed to
static_proxy
or its method decorators must have been imported using the import hook, not dynamically withjclass
.Nested classes can be referenced by importing the top-level class and then using attribute notation, e.g.
Outer.Nested
.The names bound by the
import
statement must be used directly. For example, afterfrom java.lang import IllegalArgumentException as IAE
, you may useIAE
in athrows
declaration. However, if you assignIAE
to another variable, you cannot use that variable in athrows
declaration, as the static proxy generator will be unable to resolve it.The static proxy generator does not currently support relative package syntax.
String parameters must be given as literals.
Extending
static_proxy
classes with otherstatic_proxy
classes is not currently supported. However, behaviour can still be shared betweenstatic_proxy
classes by making them inherit from a common Python base class.
Notes¶
The following notes apply to both types of proxy:
Proxy classes may have additional Python base classes, as long as the
dynamic_proxy
orstatic_proxy
expression comes first.When a Python method is called from Java, the parameters and return value are converted as described in data types above. In particular, if the method is passed an array, including via varargs syntax (“…”), it will be received as a
jarray
object.If a method is overloaded (i.e. it has multiple Java signatures), the Python signature should be able to accept them all. This can usually be achieved by some combination of duck typing, default arguments, and
*args
syntax. For example, see the methodf
in the static proxy example above.To call through to the base class implementation of a method, use the syntax
SuperClass.method(self, args)
. Usingsuper
is not currently supported for Java methods, though it may be used in__init__
.Special methods:
If you override
__init__
, you must call through to the superclass__init__
with zero arguments. Until this is done, the object cannot be used as a Java object. Supplying arguments to the superclass constructor is not currently possible.If you override
__str__
,__eq__
or__hash__
, they will only be called when an object is accessed from Python. It’s usually better to override the equivalent Java methodstoString
,equals
andhashCode
, which will take effect in both Python and Java.If you override any other special method, make sure to call through to the superclass implementation for any cases you don’t handle.
Exceptions¶
Throwing¶
java.lang.Throwable
is represented as inheriting from the standard Python Exception
class, so all Java exceptions can be thrown in Python.
When inheriting Java classes, exceptions may propagate from Python to Java code:
The exception will have a combined Python and Java stack trace, with Python frames indicated by a package name starting “<python>”.
If the exception is of a Java type, the original exception object will be used. Otherwise, it will be represented as a PyException.
Catching¶
Exceptions thrown by Java methods will propagate into the calling Python code. The Java stack trace is added to the exception message:
>>> from java.lang import Integer
>>> Integer.parseInt("abc")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
...
java.lang.NumberFormatException: For input string: "abc"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:580)
at java.lang.Integer.parseInt(Integer.java:615)
Java exceptions can be caught with standard Python syntax, including catching a subclass exception via the base class:
>>> from java.lang import IllegalArgumentException
>>> try:
... Integer.parseInt("abc")
... except IllegalArgumentException as e:
... print type(e)
... print e
...
<class 'java.lang.NumberFormatException'>
For input string: "abc"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:580)
at java.lang.Integer.parseInt(Integer.java:615)
Multi-threading¶
The global interpreter lock (GIL) is automatically released whenever Python code calls a Java method or constructor, allowing Python code to run on other threads while the Java code executes.
If your program contains threads created by any means other than the Java Thread API or the Python
threading
module, you should be aware of the following function:
-
java.
detach
()¶ Detaches the current thread from the Java VM. This is done automatically on exit for threads created via the
threading
module. Any other non-Java-created thread which uses thejava
module must calldetach
before the thread exits, or the process may crash.
See also
Cross-language issues relating to multi-threading.